Data Engineering at Enfycon in Irving

Title: Full Stack Data Engineering Developer
Duration: C2H
Location: Irving, TX (Local must || F2F)

Position:

HIGHLIGHT - Candidate must have data bricks, SQL, Pyspark and python, preferred .net, C#, Angular. This is a data intense position that has performance tuning, ETL processes. This is not an architect or lead position it is hand-on dev work. They need to be able to solve, they can use tools in their onsite interview to find the solution but have to be able to explain why they went the route they chose...they must also talk about their previous experience in why they chose the route to solve and logic.

Summary:
In this role, you will design, develop, and support scalable data and database solutions that enable analytics and innovation across healthcare-focused client initiatives. You will collaborate with cross-functional teams to build modern data pipelines, optimize relational databases, and contribute to cloud-based data platforms. You will apply strong SQL and Python expertise to enhance performance, reliability, and data accessibility while supporting advanced analytics and Artificial Intelligence/Machine Learning (AI/ML) use cases.
Responsibilities:

• Design, build, test, and optimize relational database solutions using SQL Server and Azure SQL, including T-SQL queries, stored procedures, and data models.
• Improve database performance, reliability, and scalability through indexing strategies, query tuning, and optimization techniques.
• Develop and maintain scalable Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT) processes to integrate data across cloud-based platforms.
• Build and support data pipelines and workflows using Azure SQL, Databricks, Apache Spark, Python, and Pyspark.
• Design and implement relational and dimensional data models, including Slowly Changing Dimension (SCD) patterns.
• Support AI/ML initiatives by developing and maintaining data pipelines and feature datasets used for model training and analytics.
• Utilize Python to enable data preparation, analytics workflows, and experimentation for machine learning use cases.
• Collaborate with data science teams to operationalize models using Spark, ML frameworks, or cloud-based ML services.
• Participate in design discussions, code reviews, and Agile ceremonies to ensure high-quality and maintainable solutions.
• Partner with application developers, data engineers, BI teams, and analytics partners to deliver integrated solutions.
• Troubleshoot production issues, conduct root cause analysis, and implement sustainable resolutions.
• Adhere to data governance, security, and quality standards to ensure compliance and data integrity.

Qualifications:
• 7+ years of relevant experience required.
• Experience developing and supporting database solutions using SQL Server or Azure SQL required.
• Strong proficiency in T-SQL, including query development, performance tuning, and optimization required.
• Hands-on experience using Python for data processing, analytics, or data engineering workflows required.
• Experience with Databricks, Apache Spark, or similar distributed data processing platforms required.
• Understanding of data warehousing concepts, dimensional modelling, and ETL/ELT pipelines required.
• Experience working in Azure cloud environments required.
• Experience with .Net, C#, .Net Core, Angular and AI/ML preferred.
• Strong analytical, problem-solving, and written and verbal communication skills.
• Relevant degree preferred. Bachelor’s degree in computer science, Information Systems, or a related field preferred.